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Early Recognition of Smoke in Digital Video

机译:数字视频中烟雾的早期识别

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摘要

This paper presents a method for direct smoke detection from video without enhancement pre-processing steps. Smoke is characterized by transparency, gray color and irregularities in motion, which are hard to describe with the basic image features. A method for robust smoke description using a color balancing algorithm and turbulence calculation is presented in this work. Background extraction is used as a first step in processing. All moving objects are candidates for smoke. We make use of Gray World algorithm and compare the results with the original video sequence in order to extract image features within some particular gray scale interval. As a last step we calculate shape complexity of turbulent phenomena and apply it to the incoming video stream. As a result we extract only smoke from the video. Features such shadows, illumination changes and people will not be mistaken for smoke by the algorithm. This method gives an early indication of smoke in the observed scene.
机译:本文提出了一种无需增强预处理步骤即可直接从视频中检测烟雾的方法。烟雾的特征是透明度,灰色和运动不规则,这些很难用基本图像特征来描述。在这项工作中提出了一种使用颜色平衡算法和湍流计算的强健烟雾描述方法。背景提取被用作处理的第一步。所有移动的物体都是烟雾的候选者。我们使用灰度世界算法,并将结果与​​原始视频序列进行比较,以提取特定灰度范围内的图像特征。最后一步,我们计算湍流现象的形状复杂度,并将其应用于传入的视频流。结果,我们仅从视频中提取烟雾。该算法不会将阴影,照明变化和人为误发等特征误认为是烟雾。该方法可以早期指示观察到的场景中有烟雾。

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